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Hydrogen bond acidic polymers for surface acoustic wave vapor sensors and arrays

机译:用于表面声波蒸汽传感器和阵列的氢键酸性聚合物

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Four hydrogen bond acidic polymers are examined as sorbent layers on acoustic wave devices for the detection of basic vapors. A polysiloxane polymer with pendant hexafluoro-2-propanol groups and polymers with hexafluorobisphenol groups linked by oligosiloxane spacers yield sensors that respond more rapidly and with greater sensitivity than fluoropolyol, a material used in previous SAW sensor studies. Sensors coated with the new materials all reach 90% of full response within 6 s of the first indication of a response. Unsupervised learning techniques applied to pattern-normalized sensor array data were used to examine the spread of vapor data in feature space when the array does or does not contain hydrogen bond acidic polymers. The radial distance in degrees between pattern-normalized data points was utilized to obtain quantifiable distances that could be compared as the number and chemical diversity of the polymers in the array were varied. The hydrogen bond acidic polymers significantly increase the distances between basic vapors and nonpolar vapors when included in the array. [References: 40]
机译:四种氢键酸性聚合物作为声波设备上的吸附剂层被检测出来,用于检测基本蒸气。具有低级六氟-2-丙醇侧基的聚硅氧烷聚合物和具有通过低聚硅氧烷间隔基连接的具有六氟双酚基团的聚合物所产生的传感器比以前的SAW传感器研究中使用的材料多元醇响应更快,灵敏度更高。在首次显示响应后的6 s内,涂有新材料的传感器全部达到90%的完全响应。当阵列不包含氢键酸性聚合物时,将无监督学习技术应用于模式归一化传感器阵列数据,以检查蒸气数据在特征空间中的扩散。利用图案归一化数据点之间以度为单位的径向距离来获得可量化的距离,可以将其进行比较,因为阵列中聚合物的数量和化学多样性会发生变化。当包括在阵列中时,氢键酸性聚合物显着增加了碱性蒸气和非极性蒸气之间的距离。 [参考:40]

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